This web page was produced as an assignment for an undergraduate course at Davidson College.
Introduction |
Analysis of Figures |
Conclusion and References |
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Genetically identical cells and organisms show remarkable diversity and variation in phenotypic traits even when exposed to similar environmental conditions. The concept of noise in gene expression accounts for some of this variation in genetically identical populations. Random fluctuation in the transcription and translation of genes is a specific example of phenotypic noise that accounts for phenotypic variation among genetically identical populations.
Freed et al. studied phenotypic noise through a global analysis of expression levels of a reporter gene “attached” to different promoters in S. Typhimurium. In the past most research concerning noise in gene expression focused on analysis of single biological traits. Freed and his colleagues wished to create a method that would determine genes whose expression varied stochastically over a particular time period. Freed’s approach looked for noise in many genes, giving the researchers a global perspective of the organism and a measurable relativity of noise levels between different genes and their regulatory promoters.
The methodology behind the method to globally explore gene expression noise is quiet simple and ingenious. Freed et al. created a promoter library by partially digesting S. Typhimurium and fusing these fragments upstream of the GPR reporter gene in a plasmid. Researchers equally divided the culture of the plasmid library into an experimental and control groups, with five populations in each group. They repeated fluctuating random selection on all 5 experimental populations 7 times, measuring GFP expression through fluorescence-activated cell sorting (FACS). During such repeated fluctuating selection, they selected clones with the highest 5% GFP expression, grew the selection clones, and then selected the clones from this new population with the lowest 5% GFP expression (as measured by fluorescence). By alternating selection directions for GFP expression (high, low, high, low, ect.), the researchers were able to sift out the promoters that exhibit the most noise. The 5 control populations also underwent FACS sorting, but there was no specific selection made based on GFP expression levels. Instead, the control populations represent a random subset of cells accounting for the entire GFP expression range.
The researchers went on to test the robustness of their newly developed method by determining: 1). the stable nature of phenotypic noise in the selected populations, 2). the genes associated with the phenotypically noisy promoters in S. Typhimurium, specifically establishing the contingency in the promoter’s noise when in its native locus and when associated with its original gene, 3).that phenotypic noise was not due to genetic phase variation and finally 4). the possible biological functions for phenotypic noise.
The following web page outlines the figures shown in Freed et al.’s paper and expresses my opinion on the paper.